Machine Learning-Based Blood RNA Signature for Diagnosis of Autism Spectrum Disorder.

ABSTRACT: Early diagnosis of autism spectrum disorder (ASD) is crucial for providing appropriate treatments and parental guidance from an early age. Yet, ASD diagnosis is a lengthy process, in part due to the lack of reliable biomarkers. We recently applied RNA-sequencing of peripheral blood samples from 73 American and Israeli children with ASD and 26 neurotypically developing (NT) children to identify 10 genes with dysregulated blood expression levels in children with ASD. Machine learning (ML) analyzes data by computerized analytical model building and may be applied to building diagnostic tools based on the optimization of large datasets. Here, we present several ML-generated models, based on RNA expression datasets collected during our recently published RNA-seq study, as tentative tools for AS

SUBMITTER: Voinsky I 

PROVIDER: S-EPMC9916487 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature